Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence.This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities.The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities.     

A transient stochastic simulation–optimization model for operational fuel planning in-theater

Army fuel planners are responsible for developing daily loading plans that specify which tankers to load, with what fuel, and where to send the loaded tankers. The tools used to accomplish this task are custom built spreadsheets which require large amounts of time and effort to use, update, and keep free of errors. This research presents a transient stochastic simulation–optimization model of the in-theater bulk fuel supply chain, where the simulation model is used to simulate the performance of the fuel supply chain under a particular fuel distribution policy and the optimization portion is used to update the policy so that it results in the performance desired by the Army fuel planner. The fuel distribution policy can then be used to derive the daily loading plan. Due to the multi-objective nature of the problem, the set of policies that form the efficient frontier are all candidate policies for the Army fuel planner to select from. Results of experimentation with a wide variety of supply chain scenarios indicate that, for a given supply chain scenario, the optimization portion of the model identifies a set of fuel distribution policies that address the objectives of the Army fuel planner. In addition, the simulation–optimization model comfortably solves the largest supply chain scenarios the Army fuel planner would reasonably be expected to encounter.     

震后应急物流系统中带时间窗的模糊动态LRP

针对震后应急物流系统中多层次设施定位－运输路线安排问题(LRP),考虑系统中的动态性、时效性、路网连通性、需求不确定性等特点,建立了一个带时间窗的模糊动态LRP优化模型,据此进行救援过程中不同周期灾区外围应急物资集散点和灾区应急配送中心的定位以及应急物资运输路线安排的联合决策。针对该模型的特点,提出了一种基于动态规划的改进遗传算法,为防遗传算法过早收敛问题,使用了随机遍历抽样法、重组策略和变化变异率法,并通过特定实值编码、罚函数法和物资需求量分割策略处理模型中的约束条件。最后,通过算例分析验证了该模型和算法的有效性。     

订单融资业务风险等级评价研究

订单融资是一种新兴融资方式,评定其风险等级具有重要意义。该文以“订单”为引线,分析不同阶段风险,构建了两阶段风险等级评价模型。风险评价分为两个阶段:第一阶段通过两个一级指标判断业务订单真实性。第二阶段构建了包括主体信用、质押率、订单履行能力、库存等的指标体系,并详细阐述了各种不同指标的测定方法,运用指数函数、余弦函数、幂函数等处理方法,将各类定量指标统一投影到0-10分;然后分别运用ANP法和AHP法确定各类指标权重,构建风险等级评价模型,将风险分为5个等级。该模型可以为金融机构贷款决策提供帮助,且该文提出的分段函数等定量指标归一化方法、结合实例介绍ANP法计算原理,对于其他学者均有参考价值。     

物流园区转型升级风险评价及对策

我国产业正处于转型升级的关键期,因此研究物流园区转型升级风险评价,并提出有针对性的对策措施具有十分重要的意义。本文针对我国物流园区转型升级中风险关联因素,首先构建了评价指标体系,并应用主成分分析对评价指标进行了降维处理,其次应用模糊综合评判法计算了各个因素的风险值,梳理出转型升级过程中的主要风险因素,并分析了主要风险因素产生的原因,最后讨论了针对主要风险因素的防范对策。     

集装箱码头堆场翻箱与外集卡提箱顺序同步优化方法

针对集装箱码头提箱作业过程中,由于外集卡的提箱顺序与目标箱在堆场的堆存位置不匹配导致大量翻箱这一难题,以码头的作业成本和外集卡的延误成本之和最小为目标,建立堆场翻箱与外集卡提箱顺序同步优化模型,优化外集卡的提箱顺序、龙门吊的任务分配以及翻箱方案。设计基于动态规划的启发式算法求解模型,并利用算例对模型与算法的有效性进行了验证。结果表明:与目前码头普遍采用的提箱方式相比,通过调整外集卡提箱顺序并同时优化翻箱方案以及龙门吊的任务分配可以降低堆场翻箱率,减少龙门吊的移动成本,从而节省提箱作业的总成本。     

基于物联网的高效安全快递自取系统设计与实现

针对物流行业投送环节存在的“最后一公里”问题,设计并实现了一种基于物联网的高效安全快递自取系统。该系统综合利用物联网、嵌入式、传感器、GPRS等技术,快递自取箱终端以嵌入式微处理器S3C6410为主控器,实现扫码自主存件、短信自动通知客户、验证码校验自助取件、异常邮件处理以及紧急报警等功能,经过测试,该系统在实际环境中运行稳定,能够高效、安全、快捷的完成投送,可广泛布设于小区、单位等公共场所,具有十分广阔的市场应用价值。     

供给能力一定条件下的物流网络优化研究

第三方物流为了给客户提供正确且高效的服务,对物流进行了领域整合,建立了连接供应商和顾客的多级物流网络,网络包括了运输、流通加工、储存及配送等物流子系统。为降低网络系统成本,提高服务效率,针对网络中节点和通道上固定的物流供给能力,设计了以运营成本为目标的优化模型,通过变分不等式求出了最佳的物流组织方案,同时根据运行方案对网络中基础设施进行了重新设计改造,避免了资源不必要的浪费。最后通过算例对模型和算法进行了验证。     

基于微分对策的第三方回收再制造闭环供应链回收策略研究

动态环境下,研究了第三方回收的再制造闭环供应链最优控制策略。建立产品回收率为状态变量的微分方程,分别构建了集中式决策和第三方回收下的闭环供应链模型,利用最优控制和微分对策理论求解并得到供应链各方的最优控制策略。对最优策略进行分析发现:(1)系统的产品回收率随时间的推移而增加;(2)产品的零售价格和批发价格随时间减小,最优回收努力投入随时间增加;(3)相对于集中式决策,第三方回收下闭环供应链系统的产品回收率较低,产品市场价格较高,而市场需求较小。     

A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

With a typical investment in excess of £100 million for each project, the installation phase of offshore wind farms (OWFs) is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined framework, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.